The answer is to automatically apply deidentification transformations to sensitive columns. This is correct because Cloud DLP inspection jobs first scan BigQuery tables to classify sensitive data types like PII or credit card numbers using built-in infoTypes, and then deidentification transformations such as masking or tokenization can be applied directly to those columns to protect the data at rest. On the Google Professional Cloud Security Engineer exam, this tests your understanding of the full data protection workflow—inspection, classification, and deidentification—as a continuous pipeline rather than isolated steps. A common trap is assuming that simply classifying data is sufficient, but the exam emphasizes that deidentification must be actively applied to reduce risk. Remember the memory tip: “Inspect, classify, then deidentify—never leave sensitive data unguarded.”
PCSE Ensuring data protection Practice Question
This PCSE practice question tests your understanding of ensuring data protection. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
Which THREE of the following are best practices for using Cloud DLP to protect sensitive data in BigQuery?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "best"
Why it matters: Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use inspection jobs to scan tables and identify sensitive data.
Option A is correct because Cloud DLP inspection jobs can scan BigQuery tables to identify sensitive data types (e.g., PII, credit card numbers) using built-in infoTypes. This is a foundational step before applying any deidentification or access control measures, as it allows you to discover where sensitive data resides.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✓
Use inspection jobs to scan tables and identify sensitive data.
Why this is correct
Inspecting data is a foundational step for data protection.
Clue confirmation
The clue word "best" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
Store transformed data in a separate dataset with stricter access controls.
Why it's wrong here
This is an architectural choice, not a DLP best practice.
✓
Use DLP to classify data and then apply access controls based on data classification.
Why this is correct
Classification-based access is a recommended approach.
Clue confirmation
The clue word "best" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✓
Automatically apply deidentification transformations to sensitive columns.
Why this is correct
Automation ensures consistent protection.
Clue confirmation
The clue word "best" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
Encrypt the entire BigQuery table using CMEK.
Why it's wrong here
Encryption is important but not a DLP-specific best practice.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google Cloud often tests the distinction between data discovery/inspection (DLP) and data protection mechanisms like encryption (CMEK) or access control (IAM), leading candidates to confuse complementary security controls with DLP-specific best practices.
Detailed technical explanation
How to think about this question
Cloud DLP uses inspection templates that can be configured with custom infoType detectors and likelihood thresholds to scan BigQuery tables. The inspection results can be used to trigger deidentification transformations (e.g., masking, tokenization) via DLP jobs or to feed into BigQuery column-level security policies. A real-world scenario is a healthcare organization scanning patient records for PHI before applying deidentification to comply with HIPAA.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A company's IT admin needs to give a contractor read-only access to production logs without sharing account credentials. Using role-based access control (RBAC) and temporary scoped permissions — not a permanent shared password — is the correct pattern. Questions like this test whether you can apply least-privilege access across cloud identity services.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Ensuring data protection — This question tests Ensuring data protection — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use inspection jobs to scan tables and identify sensitive data. — Option A is correct because Cloud DLP inspection jobs can scan BigQuery tables to identify sensitive data types (e.g., PII, credit card numbers) using built-in infoTypes. This is a foundational step before applying any deidentification or access control measures, as it allows you to discover where sensitive data resides.
What should I do if I get this PCSE question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Are there clue words in this question I should notice?
Yes — watch for: "best". Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. An organization uses Cloud DLP to inspect BigQuery tables for sensitive data. They want to automatically remove credit card numbers before the data is accessed by analysts but still allow the raw data for auditing purposes. Which DLP technique should they use?
easy
A.De-identification transform with masking
B.Re-identification transform with tokenization
✓ C.De-identification transform with redact
D.De-identification transform with replacement
Why C: Option C is correct because the 'De-identification transform with redact' completely removes sensitive data (like credit card numbers) from the output, ensuring analysts never see the raw values while the original data remains intact in the source BigQuery table for auditing. This aligns with the requirement to automatically strip sensitive content before access, without altering the stored data.
Last reviewed: Jun 30, 2026
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This PCSE practice question is part of Courseiva's free Google Cloud certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the PCSE exam.
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